Solution processed TiO₂ anatase film was used as sensitive layer for H₂ detection for two plasmonic sensor configurations: A grating-coupled surface plasmon resonance sensor and a localized surface plasmon resonance sensor with gold nanoparticles. The main purpose of this paper is to elucidate the different H₂ response observed for the two types of sensors which can be explained considering the hydrogen dissociation taking place on TiO₂ at high temperature and the photocatalytic activity of the gold nanoparticles.

Soil moisture plays a crucial role in landslide research as it directly influences slope stability and the occurrence of landslides. The amount of water present in the soil significantly impacts its strength and cohesion. Excessive soil moisture, especially during periods of heavy rainfall, can reduce the frictional resistance within the soil, leading to a decrease in shear strength and an increased likelihood of landslides. The province of Lower Austria is situated in a region highly prone to landslides due to its specific geological characteristics. The prevailing geological formations consist mainly of the Flysch and the Klippen Zone, characterized by mechanically weak units comprising intercalated limestones and deeply weathered materials. These geological conditions, coupled with hydrological factors, changes in land use, and various anthropogenic influences, collectively contribute to the inherent instability of the region.Monitoring and understanding soil moisture levels provide valuable insights into the predisposing and triggering factors, potentially enhancing the prediction and mitigation of these hazardous events. Advancements in technologies like Cosmic Rays Neutron Sensing (CRNS) enables to obtain spatially averaged soil moisture measurements, offering a more comprehensive understanding of moisture distribution across different scales. The defining characteristic of (CRNS) technology lies in its ability to directly measure water content, naturally averaged within a volume known as the footprint. This volume encompasses a horizontal extension with a radius spanning up to hundreds of meters and penetrates the soil to depths of tens of centimeters. This is widely acknowledged as the primary advantage of the CRNS probe compared to point-scale measurements, as it yields a valuable representative value for water availability in the designated area. In this study, we apply CRNS at a slow-moving landslide in Lower Austria and explore its potential.

Cosmic Ray Neutron Sensing (CRNS) is a ground based technique that utilises epithermal neutron measurements as a proxy for environmental hydrogen content. Similarly, to other ground based cosmic ray detectors (e.g. neutron monitors), CRNS detectors observe the solar cycle and space weather events. Typically, these effects must be corrected, but CRNS detectors have also been specifically used to observe space weather. The specific sensitivity of CRNS detectors to the primary spectrum and the relationship to other cosmic ray measurements is not fully understood. During the maximum of solar cycle 25 a latitude survey utilising a mini neutron monitor (MNM), two CRNS detectors of different design and a muon telescope was undertaken onboard the German Research Vessel Polarstern. The observations are used to derive differential response functions and yield functions for two neutron detectors. While the differential response, between neutron detectors is similar, it strongly deviates between muon and neutron detectors. The yield functions of CRNS and MNM are in good agreement with each other, indicating that CRNS detectors and MNM observe a comparable range of the primary cosmic ray spectrum.

Cosmic Rays Neutron Sensing (CRNS) is a method to derive the amount of water in the environment by the measurement of neutron albedo in the proximity of the soil. The signal is strongly affected by the incoming cosmic rays modulation, requiring a continuous real-time correction that is typically achieved by taking as a reference the observations provided by the Neutron-Monitor DataBase (NMDB). Using the incoming flux of muons as a reference has been proposed as an alternative method of correction by Finapp, whose CRNS detector is capable of contextually measuring both neutrons and muons.What is noise for some can be signal for others, which leads to increasing collaboration between the CRNS and the Space Weather communities. While CRNS devices cannot provide a level of accuracy and resolution comparable to dedicated neutron monitors, they would compensate with the number of deployed detectors. Being low-cost, easy to install and maintain, their use is spreading fast for various purposes, from agriculture to environmental monitoring. This can be seen as a low-cost world-wide diffuse observatory, potentially with a much higher spatial density than the NMDB and spontaneously growing.Assessing how neutron and muon count rates measured by these devices are affected by space weather events, like Forbush decreases or Ground-Level Enhancements (GLE), could increase the understanding and monitoring of such events by providing a mapping of their impact on the Earth surface. If the CRNS station is equipped with a Finapp detector, the contextual detection of muons can provide additional information.In this presentation we will analyze how a small set of Finapp CRNS probes, located in different locations of Earth, responded to some major events of Furbush decrease or GLE, in the neutron and muon count rate signals. The set includes, among others, two probes located in NMDB sites (OULU and JUNG) and a probe installed in Svalbard. This aims to be an example of the potential interest of CRNS for Space Weather investigation. A large database of collected data may be already available and underused.AcknowledgementWe acknowledge the NMDB database (www.nmdb.eu), founded under the European Union's FP7 programme (contract no. 213007) for providing data. Jungfraujoch neutron monitor data were kindly provided by the Physikalisches Institut, University of Bern, Switzerland. Oulu neutron monitor data were kindly provided by the Sodankyla Geophysical Observatory (https://cosmicrays.oulu.fi). CaLMa neutron monitor data were kindly provided by the Space Research Group (SRG-UAH), University of Alcala, Spain.

It is widely recognised that the ability of measure Soil Water Content (SWC) is crucial to improve early warning systems for environmental hazards like floods, droughts, landslides, avalanches and wildfires. However, hydrological variables are notably more difficult to measure than meteorological variables. Common technologies to measure SWC are invasive point-scale probes, which are hardly representative of a wider area, unsuitable for coarse-textured soils and easy to be broken or lost. The main alternative is remote sensing, which suffers limits related to spatial resolution, measurement depth and continuity.As an attempt to compensate for the lack of measurements of hydrological variables, computational models are widely used to derive them from meteorological ones. For example, the Canadian-developed Fire Weather Index (FWI) relies mainly on precipitations and temperature to evaluate the dryness of the soil. Indeed models still need to be validated and improved using measured data.Proximal sensors based on the concept of Cosmic Rays Neutrons Sensing (CRNS) emerged as a reliable option for non-invasive measurement of SWC, within a large footprint (hectares), in depth (tens of cm) and with sub-daily resolution. CRNS is based on the detection of neutrons, which are generated in the atmosphere by the interaction of cosmic rays (high energy particles naturally flowing from space), then backscattered by the soil and effectively absorbed by water, due to their strong interaction with hydrogen. CRNS systems can easily be integrated in meteorological stations and operate autonomously also in remote areas, while transmitting the data for a real-time monitoring.In the framework of the MOSAIC Project*, six CRNS systems manufactured by Finapp were installed in sites selected to span different altitudes vegetation types and exposures, integrating them into pre-existent meteorological stations. Computation of the FWI is also available for the same sites. We will compare the information provided by the CRNS with the output of the FWI and discuss how the model can be improved by integrating the SWC measurement.*This work is part of the MOSAIC Project (Managing prOtective foreSt fAcIng clImate Change compound events), co-funded by the European Union through the Interreg Alpine Space programme (Project ID: ASP0100014), and it involves the use of data provided by courtesy of ARPAV (Dipartimento Regionale per la Sicurezza del Territorio).

Cosmic Rays Neutron Sensing (CRNS) is a well-known method in Hydrology that allows to measure soil water content on a large scale and in depth. It is based on the detection of cosmogenic neutrons, particles generated by the interaction of cosmic rays with the atmosphere, after their interaction with the soil where they can be effectively absorbed by water molecules. The signal collected by a single CRNS probe in terms of neutron count rate is sensitive to soil moisture within a volume spanning up to a dozen hectares and up to 50 cm depth, in real-time, positioning itself in a horizontal spatial scale in between point measurements and satellites.In order to evaluate the effectiveness of CRNS to give information about soil moisture in an agricultural system with different soil conditions, a site in the Alto Monferrato vine-growing area (Piedmont, NW Italy) was equipped with a Finapp CRNS probe since August 2023. The site has two vineyard-field-scale plots with inter-rows managed with conventional tillage (CT) and grass cover (GC), respectively. More than 20 sensors are located in different positions and depths (from 10 to 50 cm) in the vineyard, including the STEMS network that is part of the International Soil Moisture Network. Precipitation measurements on site are available over more than 20 years, show that 2023 was very dry, with Standardized Precipitation Index lower than -1 for most of the year, whereas 2024 was increasingly wet, with exception of first two months of the year.Available soil moisture data from CRNS and sensors have been compared until autumn 2024, using statistical indexes such as the efficiency coefficient of Nash and Sutcliffe (NSE), root mean square error of residuals (RMSE) and the coefficient of determination of the linear regression (R2). The analysis was carried out separately for the two years, which were considered respectively dry and wet.Statistics showed that in the last 5 months of 2023 (dry period) there was a good agreement of soil moisture values measured by sensors between 10 and 20 cm of depth with both soil management, with different results according to the position, the best reported in the middle of the GC inter-row at depth of 20 cm (R2=0.913, NSE=0.756, RMSE=0.25). The results for 2024, which was a wetter year, showed great variability, such as the values recorded by the sensors, with unsatisfactory statistics, since best values for indexes were obtained for the sensor placed in the middle of CT inter-row (R2=0.598, NSE=0.485, RMSE=0.118).Thus, in the dry period the CRNS probe gave good information on soil moisture conditions in the most superficial layer disregarding the soil management of the vineyard. On the contrary, the difficulty in having good agreement in wet conditions can be due to the high spatial variability of soil moisture both in the horizontal and in-depth directions, soil saturation and ponding, in addition to variable conditions of soil conditions (i.e. soil density) depending to soil management and tractor traffic during the growing season.